Why We Should Let AI Start Over
▼ Summary
– Tech leaders like Sam Altman and Mark Zuckerberg acknowledge a potential AI bubble but see underlying value and growth potential.
– The author expresses uncertainty about how an AI bubble might burst but hopes AI will become a normal, stable technology.
– Normal technologies are characterized by steady development and skill-building, unlike volatile bubble technologies that change constantly.
– The author’s “C/B ratio” (conferences to blogging) measures technology maturity, with current AI dominated by conferences rather than blogging.
– The AI industry’s reliance on major companies creates a fragile ecosystem where a failure could cause widespread collapse of startups.
Navigating the current state of artificial intelligence feels like walking a tightrope between boundless potential and sobering reality. Tech leaders like Sam Altman and Mark Zuckerberg have openly acknowledged the possibility of an AI bubble, while urging a tempered perspective on artificial general intelligence. Their caution reflects a broader industry sentiment that we’re balancing on a fragile edge, one where immense promise coexists with the risk of sudden deflation.
Speculation runs rampant about how this bubble might burst. Will public interest in large language models fade as quickly as it appeared? Could a breakthrough drastically lower development costs, flooding the market with affordable alternatives? Or will the collapse manifest in plunging stock prices and panicked traders? The truth is, no one can predict the exact trigger, but many of us share a quiet hope: that AI will soon transition from a speculative frenzy into something stable and integrated, a normal technology.
There’s something deeply reassuring about mature, established technologies. They come with documentation. They evolve at a manageable pace, allowing individuals and industries to build expertise and workflows around them. In contrast, bubble-era technologies shift constantly, creating uncertainty about whether they’ll reshape society for better or worse. While analysts often rely on financial metrics to gauge maturity, I prefer a simpler, self-devised indicator: the conference-to-blogging ratio. When a field is dominated by events and summits, it’s still in its volatile, hype-driven phase. When thoughtful, technical blog posts become the primary medium of discourse, it has normalized.
Right now, the AI landscape is saturated with conferences, sponsored meetups, and high-profile gatherings. Venture capital firms eagerly fund these events, turning them into stages for dominance displays and networking, often communicated through endless PowerPoint decks. Meanwhile, substantive, detailed blog content remains scarce. This imbalance reveals a lot about where AI stands: it’s still a field where people are figuring out their place in the pecking order, rather than settling into steady, shared understanding.
Looking back, the so-called golden age of blogging emerged not just from passion, but from necessity. When funding is scarce, writing online becomes the most accessible way to exchange ideas. As startup budgets shrink and speculative money evaporates, extravagant conferences are often the first expense to be cut. That’s when experts and enthusiasts turn back to blogging, not for clout, but for clarity. It’s through writing that we refine our thoughts and establish our identities within a fast-moving domain. Someday, AI’s conference-to-blog ratio will inevitably tip toward the latter.
We’re not there yet, and the road ahead may be long. Today’s global economy resembles a vast suspension bridge, supported by a handful of foundational players, OpenAI, Nvidia, and Google act as critical anchor points, upholding grand promises of planetary AI transformation. Should any of these pillars weaken, even slightly, the entire structure could falter. Countless startups, mine included, are perched on that bridge, aware that a single misstep could send everything tumbling into uncertainty. Living with that tension has become one of the defining experiences of this moment, a mix of exhilaration and unease that makes every breakthrough and every setback feel profoundly consequential.
(Source: Wired)
